Exploring gender differences in Malaysian urban adolescent Internet usage
First Monday

Exploring gender differences in Malaysian urban adolescent Internet usage by Patrick C-H Soh, Boon Heng Teh, Yong Hoe Hong, Tze San Ong, and John P. Charlton

This study explored gender differences in urban adolescent Internet access, usage and motives. Data were collected from 914 urban school students in Malaysia. Factor analysis revealed that eroticism, entertainment, social–interaction, shopping and information/surveillance are the key drivers for adolescence Internet usage. No differences between boys and girls were detected in Internet accessibility and home computer ownership. Boys and girls differed in their intensity of usage, place of access and their motivations to use the Internet. Girls were more motivated by social–interaction, shopping and surveillance/ information, while boys were more motivated by eroticism and had a higher tendency to be addicted to the Internet. However, boys and girls did not exhibit any significant differences in online entertainment motivation.


Theoretical framework
Data analysis




Across the world, technology and the Internet are enabling great changes. Consequentially, people lacking Internet access are likely to miss out on knowledge, opportunities and advancement and face severe economic, social and political deprivation, with little prospects of catching up. On the other hand, research has reported that Internet users enjoy considerable academic, financial, social and economic benefits (Anderson, et al., 1995; University of Southern California’s Annenberg School Center for the Digital Future, 2005). Also, females have generally been found to lag behind males in embracing technology and the Internet (Kraut, et al., 1996; Pavlik, 1998), and this disparity is important given that gender equality in terms of women and men enjoying the same rights, resources, protection and opportunities is an important human rights issue (Helspar, 2010).

The two genders also use the Internet differently and understanding differences between the genders’ Internet access, motivations and behaviour is important. Such knowledge provides authorities, parents and teachers with the information necessary to insightfully guide youths’ Internet usage and to help them avoid online dangers, and can also help marketers to more accurately target their messages. Finally, understanding the gender disparity in access and usage may also help to explain the shortage of qualified female ICT professionals (Trauth and Howcroft, 2006).

Malaysia is a peaceful and prosperous southeast Asian country, and has a cross–cultural population of Malays, Chinese and Indians of almost 28 million people. The Internet penetration rate is 60.7 percent (Internet World Stats, 2013) and females lag behind males in terms of Internet usage (ASEAN Connect, 2005) and wages (Schafgans, 2000), although gender equality exists in the number of home Internet users (Malaysian Communications and Multimedia Commission, 2005). With an Internet penetration rate of 90 percent among Malaysian urban youths (Soh, et al., 2012) no great gender disparity would be expected among such youth. Nevertheless, little is known about gender differences in Internet motivations, use and addiction within this demographic group, few studies appearing to exist in this area. While Charlton, et al.’s (2012) study on religiosity, Internet usage and addiction utilised the same dataset as this study, this previous study compared within gender correlations and did not consider mean gender differences. In the present study only data for urban school students were analysed. Small towns and suburban school children were excluded to remove any possible differences between urban and small town/suburban youths. Hence, the study sought to explore gender differences in Malaysian urban adolescents’ Internet access, usage and motives.



Theoretical framework

The primary theoretical foundation for this study is the uses and gratifications model (U&G). This model is a key theory that explains why people choose to use particular types of media. According to the theory, people select a specific medium to gratify their goals and needs (Blumler, 1979; Katz, et al., 1974). Many studies have employed the U&G model to explain usage of the Internet and Internet–related communication (Katz, et al., 1974; Papacharissi and Rubin, 2000).

According to Table 1, the two highest–ranked Internet usage motives are entertainment and social–interaction, particularly for youth (Abdulla, 2003; J. Choi, et al., 2004; Y.J. Choi, 2001; Huang, 2004; Kwon, 2003; Mitchell, 1999; Papacharissi and Rubin, 2000; Park, 2004; Song, et al., 2004; Sun, 2004; Wang, 2006). Shopping/product information motives are also prominent in the findings of many studies, though not all. However, the studies which did not find shopping/product motivations to be salient mostly used lists of gratifications from previously studied media such as television, and failed to include motivational items involving the desire to “to buy things” and “to get product information” (see Wang, 2006; Sun, 2004). Additionally, some of these studies were conducted prior to the popular commercialisation of the Web (see Charney, 1996), the more recent technological development of the Web giving rise to new acquisitive gratifications.

The compilation of Uses and Gratifications Internet studies in Table 1 reveals that Internet motivations can be grouped into four key categories, namely social–interaction, entertainment, information and surveillance and online shopping. Note that, although online pornography is not particularly prominent in Table 1, as technology advances in realism and multimedia capabilities, the Internet is fast becoming a major channel for the dissemination of pornography. Consequentially, eroticism is increasingly being identified as an additional key Internet motive by non–U&G studies (Hong, et al., 2007; Meerkerk, et al., 2006; Tsitsika, et al., 2008).


Popularity of Internet motivations from uses and gratifications studies
Popularity of Internet motivations from uses and gratifications studies


Another key theoretical foundation for this study was innovation diffusion theory. According to the innovation diffusion literature, males are more likely to embrace a new technology than females (Gandy, 1994). Historically, new technology infrastructures, such as the railroad system or the national highway system, have tended to serve firstly a society’s elite males and then only later the masses. This could be largely due to the high costs involved in the production of new infrastructure, which was then passed on to users. Given males’ dominant roles in most societies then, in the past they have been more likely than women to be able to afford the high costs (Pavlik, 1998). The dissemination of new media technologies has similarly tended to reflect the wealth inequalities in societies. Studies indicate that a variety of media technologies have often initially bypassed women, the poor, minorities and rural residents (Gandy, 1994).

Likewise, men were the early adopters of the Internet (Pavlik, 1998), and again the gender difference in socioeconomic status has been identified as a key reason for this (Bimber, 2000). Another reason for the gender difference in Internet adoption is that men tend to be more interested in technology than women (Shashanni, 1997). In one of the earliest longitudinal Internet studies, Kraut and his team (1996) concluded that males used the Internet more than females even when both were provided with free access. Hence, at least initially, a large gender divide existed with the percentage of males using the Internet being twice that of females; 26 percent vs. 13 percent respectively (Pavlik, 1998).

As the Internet has gained popular acceptance, the gender gap seems to have narrowed considerably (Cummings and Kraut, 2002; Fallows, 2005). In March 2000, a nationwide poll reported that the proportion of online Americans was 49 percent of males compared to 44 percent of females (Fallows, 2005). By 2005, the difference was reported to have narrowed further to a statistically insignificant two percentage points, 68 percent of men vs. 66 percent of women being online users (Fallows, 2005). Similarly, controlling for socio-economic characteristics, Ono and Zavodny (2003) concluded that the U.S. digital gender inequality had narrowed and disappeared by the year 2000, and in fact one 2005 study even reported that the percentage of online teenage girls in the U.S. surpassed that of teenage boys online (88 percent vs. 85 percent respectively; Lenhart, et al., 2005).

Outside of the U.S., the digital gender gap also seems to be narrowing. In China, the ratio of male to female online users reduced from 7:1 in 1997 to 1.6:1 by 2002 (Hung, 2003). In Singapore, the 9.4 percentage gender gap for school children in 1999 had not only disappeared by year 2001, but females surpassed males by 4.1 percentage points (Kuo, et al., 2002). In Malaysia, the authoritative ASEAN Connect (2005) reported that the gender ratio of Internet users was 6:4 male to female in year 2002, but by 2005 a national survey reported gender equality for Malaysian home Internet users (Malaysian Communications and Multimedia Commission, 2005). Hence, although a cross–gender comparison of the overall Internet usage of Malaysian youths was performed in the present study, it was not expected that a difference would be identified.

The above said, gender differences in the intensity and types of online usage seem often to persist despite the narrowing of the overall online gender gap. American males are reported to use the Internet more frequently (Li and Kirkup, 2007; University of Southern California’s Annenberg School Center for the Digital Future, 2008; Wasserman and Richmond–Abbott, 2005) and for longer durations than females (Joiner, et al., 2005; Jones, et al., 2009; Madell and Muncer, 2004). On the other hand, in a crosset al.cultural study of Chinese and British students, British male students did not spend more time online than British female students, but Chinese male students spent significantly more time online than their female counterparts (Li and Kirkup, 2007). Other studies have not detected any gender difference in the overall amount of time spend online for Singaporeans (Teo and Lim, 2000) and Americans (Fortson, et al., 2007; Jackson, et al., 2001). Also, in a study of 122 German high school students, no gender differences were detected in the diversity and frequency of Internet usage (Wolfradt and Doll, 2001). These contradictory studies mainly relied on small datasets. On the balance of the literature, the following hypotheses were proposed:

H1: Male students use the Internet more intensely than females.
H1a: Male students use the Internet more frequently than females.
H1b: Male students use the Internet for longer durations than females.

Some studies have reported that male students have significantly more years of online experience than females (Schumacher and Morahan–Martin, 2001; Jones, et al., 2009). However, a study of 261 seventh and tenth graders reported that the seventh grade males and females did not significantly differ in Internet experience unlike the tenth graders (Gross, 2004). This suggests that the gender gap in Internet experience could be narrowing, particularly as children become exposed to the Internet at a younger age. Nevertheless, the following hypothesis was proposed:

H2: Male students have more experience using the Internet than females.

Boys and girls have different motivations and use the Internet differently. Boys are more likely to use the Internet for entertainment purposes (Joiner, et al., 2005; Palesh, et al., 2004; Park, 2004; Wolfradt and Doll, 2001). Girls tend to use the Internet primarily for interpersonal communication (Colley, 2003; Jackson, et al., 2001; Madell and Muncer, 2004). Similar findings in Singapore and in Hong Kong suggest that these gender differences prevail over different cultures (Ho and Lee, 2001; Teo and Lim, 2000). In a ten–year follow–up study, Joiner, et al. (2012) reported that gender differences in different types of Internet use continued to be evident and had often grown. Males continued to use the Internet more for games and entertainment than females. In 2002 Joiner and his colleagues found no gender differences in use of the Internet for communication purposes, whereas by 2012 they discovered that females used the Internet for communication and social networking more than males. Such findings are consistent with the Pew Internet & American Life study (Lenhart, et al., 2005) which reported that teenage girls engaged more in online communication and information–seeking activities than boys. On the other hand, as might be expected, male adolescents have been shown to view Internet pornography more than females (Jones, et al., 2009; Lo and Wei, 2005; Livingstone and Bober, 2005; Ybarra and Mitchell, 2005). Nevertheless, findings of gender differences in online activities are not universal. Lin and Yu (2008) did not detect any gender difference in the motivations to use the Internet among adolescents, while Wolfradt and Doll (2001) reported gender differences in the entertainment motive but neither information nor communication motives in their rather small study of 122 German adolescent Internet users.

In general, male teenagers seem to have a higher tendency to be addicted to the Internet (Deng, et al., 2007; Soh, et al., 2007), although the converse was reported in an isolated study from Hong Kong, with female youths being shown to be more addicted than males in a study of 699 youths aged between 16 and 24 (Leung, 2004).

Based on the general consensus of findings of prior studies, the following hypotheses were proposed:

H3: Male teenagers are more motivated to use the Internet for entertainment purposes than females.
H4: Female teenagers are more motivated to use the Internet for social–interaction purposes than males.
H5: Male teenagers are more motivated to use the Internet for erotic purposes than females.
H6: Female teenagers are more motivated to use the Internet for information and surveillance purposes than males.
H7: Male teenagers are more likely to be addicted to the Internet than females.




Data from 959 survey forms were collected from students in eight randomly selected urban schools in Penang and Kuala Lumpur, the two most developed cities in Malaysia. The study sampled urban respondents only in order to eliminate any differences between urban and rural users. The survey was administered face–to–face by the lead researcher at each of the schools. The researcher gave a brief explanation of the study and informed the respondents of their rights as participants, in accordance with the American Psychological Association (APA) ethical principles for treatment of participants (APA, 1992). Although participation in the survey was voluntary and anonymous, a 100 percentage response rate was obtained. After elimination of participants providing incomplete answers and/or suspicious responses, there were 914 survey forms remaining. Of these respondents, 56 students had never used the Internet. IBM SPSS version 20 software was used to analyse the dataset.

The list of Internet motives was adapted mainly from scales used by Huang (2004) and Weiser (2000). Additional items were created for the eroticism motivation. The survey questionnaire was based on a 5–point Likert scale ranging from Strongly Disagree to Strongly Agree. The questionnaire items are listed according to their motivation dimension in Table 2 below.


Internet motives scale


Many existing Internet addiction scales fail to distinguish between high engagement and addiction, which can result in overestimation of degree of Internet addiction and the number of addicts (Charlton and Danforth, 2007). In order to address this problem, the study adopted Charlton and Danforth’s (2007) Internet addiction scale.



Data analysis

The profile of the survey respondents is shown in Table 3. The number of boy and girl respondents was roughly equivalent. The ethnic composition of Malaysia is; Malays and indigenous people 61.4 percent, Chinese 23.7 percent, Indians 7.1 percent and others 7.8 percent (Central Intelligence Agency, 2004). The ethnic composition of the three major races (Malays, Chinese and Indians) was represented in the study. However, relative to Malaysia’s population as a whole, there was a marginally higher representation of Chinese and Indians in the sample because most Chinese and Indians reside in Malaysia’s urban areas. On average, respondents were online for 10 hours a week (SD=13.4). This is comparable to the Malaysian Communications and Multimedia Commission’s (2008) survey, which reported that Malaysian home users spend an average of 12 hours a week online. Overall the percentage of respondents with home Internet access was 57.3 percent, with 45 percent having broadband access. The most frequent place of Internet access was home (55 percent), followed by cybercafés (30 percent). Twenty–seven percent of teenagers used the Internet between five and seven days a week, and 14 percent used the Internet for more than 20 hours a week.


Table 3: Profile of survey respondents.
Demographic variablesNumberPercentage
Male 445 48.7
Female 469 51.3
14 13 1.4
15 240 26.3
16 290 31.7
17 365 39.9
18 6 0.7
Malay 448 49.0
Chinese 329 36.0
Indian 119 13.0
Other 18 2.0
Muslim 448 49.0
Buddhism 264 28.9
Hinduism 91 10.0
Christianity 90 9.8
Other 13 1.4
3 257 28.1
4 284 31.1
5 373 40.8
Class stream  
Science 331 36.2
Non–science 328 35.9
Form 3 255 27.9
Parent’s highest education level  
None 8 0.9
Primary education 33 3.6
Secondary education 332 36.3
Certificate/diploma 138 15.1
Degree and above 149 16.3
Don’t know 254 27.8
Have computer at home  
Yes 713 78.0
No 201 22.0
Have Internet connection at home  
Dial–up 93 10.2
Broadband 459 50.2
No connection 362 39.6
Most frequent place of use  
Home 503 55.0
Cybercafé 274 30.0
School 32 3.5
Friend/relative’s house 45 4.9
Unspecified 60 6.6
(Includes those who do not use the Internet)
Kuala Lumpur 461 50.4
Penang 453 49.6 49.6


Table 4 shows that there was no gender difference in whether youth used or did not use the Internet, this supporting H1. Furthermore, there was no gender difference in home computer ownership. However, Table 5 shows that girls were more likely to use the Internet at home and in schools, that boys were more likely to frequent cybercafés, but that there was no gender difference in accessing of the Internet at the homes of friends or relatives.


Table 4: Gender and Internet accessibility.
Use Internet?  
Yes 418 439 F(1,912)=0.042; p>0.05
No 27 30
Computer at home?  
Yes 557 683 F(1,912)=1.690; p>0.05
No 173 178



Table 5: Gender and location of Internet use.
Mean Std. Dev. Mean Std. Dev.
Use Internet at home? 2.96 1.717 3.37 1.679 -3.234 <0.05
Use Internet at cybercafés? 2.75 1.204 2.10 1.125 7.397 <0.001
Use Internet at schools 1.75 .859 1.98 .898 -3.363 <0.05
Use Internet at friends’/relatives’ homes 2.10 1.048 2.12 1.018 -0.303 >0.05



Table 6: Gender and Internet use.
Mean Std. Dev. Mean Std. Dev.
Days use Internet 3.743 2.4411 3.216 2.2586 3.039 <0.05
Duration online 15.407 20.598 9.404 10.6826 5.041 <0.001
Online experience
(in years)
3.989 2.6621 4.128 2.2946 -0.756 >0.05


With reference to Table 6, boys used the Internet more than girls in terms of both frequency and duration. There was no significant gender difference in years of online experience. Thus, while H2a and H2b were supported H2 was not.

Factor analysis revealed that the five key Internet motives in order of significance were eroticism, social–interaction, entertainment, information/surveillance and shopping. Factor scores were tabulated for each of the motives and independent samples t–tests were used to test for gender differences in motives. The results showed that girls were more motivated by social–interaction, shopping and surveillance/information, while boys were more motivated by eroticism and were more likely to be addicted to the Internet (see Table 7). Therefore, H3 was not supported while H4, H5, H6, and H7 were supported.


Table 7: Gender, motives and addiction.
Mean Std. Dev. Mean Std. Dev.
Entertainment -0.18023 1.05 -0.7285 .969 -1.445 >0.05
Social–interaction -0.00585 1.008 0.14065 1.0015 -1.98 <0.05
Eroticism 0.58360 1.003 -0.38845 0.787611 14.737 <0.001
Surveillance/information -0.01759 0.96259 0.18040 1.0114 -2.719 <0.05
Shopping 0.08784 1.0377 -0.082 1.0427 2.218 <0.05
Addiction 26.91 8.656 25.18 8.153 2.798 <0.05





Factor analysis of the data reported that the key Internet motivations for urban youth in Malaysia are eroticism, entertainment, social–interaction, shopping, and surveillance/information. There does not seem to be any gender difference in Internet access and home computer ownership. Detailed analysis revealed that girls access the Internet more at home and in schools, while boys frequent cybercafés more. This is not surprising as in Malaysia, like other conservative Asian societies, boys are afforded more freedom to venture out of the home. Differences between the genders were not detected for Internet access via friends’ and relatives’ homes. Boys go online more frequently and for longer durations. However, there was no gender difference in number of years of online experience. Girls appear to be more motivated by social–interaction, shopping and surveillance/information uses, while boys are more motivated by eroticism and have a higher tendency to be addicted to the Internet. These results are consistent with previous findings (Joiner, et al., 2012; Lenhart, et al., 2005)

Most studies have reported that males are more motivated by entertainment gratification (Joiner, et al., 2005; Palesh, et al., 2004; Park, 2004; Wolfradt and Doll, 2001). Hence, it is surprising that this study showed that Malaysian urban teenage boys and girls have equal motivations to use the by Internet for entertainment, particularly in view that girls are online for an average of 9.4 hours compared to 15 hours for boys. A possible reason could be that girls are also driven by both social–interaction and entertainment motives when they participate in online social networking activities.

The findings generally support the view put forward by Helspar (2010) and Joiner, et al. (2005) that Internet use by males and females reflect broader trends of gender differences in society. It is useful to show that such findings generalise to Malaysia where there is a paucity of gender–related Internet studies. It is important to investigate gender differences because of the increasingly important role of the Internet in society. In particular, the findings that boys are more motivated by eroticism and are likelier to be addicted to the Internet should be of concern to parents and educators, because this might make boys particularly vulnerable to online and off–line exploitation. More studies should be undertaken to understand the online risks faced by young individuals, and any gender differences in such risks.

The interpretation of these results should to be treated with caution. Data collected for this study represents a sample of 15–17 year–old urban school children in Penang and Kuala Lumpur. Future studies could include youth from other age groups and other cities. Qualitative research using focus groups and in–depth interviews would provide deeper insights into adolescents’ online usage and motivations. End of article


About the authors

Patrick C–H Soh (Ph.D.) teaches in the Faculty of Management, Multimedia University, Malaysia and is a visiting scholar in the Singapore Internet Research Centre, Nanyang Technological University. His research interests include Internet usage, addiction, electronic commerce and business. He received his Ph.D. in Internet usage from Multimedia University and Master’s of Science Degree in Information Systems at Malaysia University of Science and Technology. Patrick would like to express his gratefulness to the Singapore Internet Research Centre, Nanyang Technological University.
E–mail: chsoh [at] mmu [dot] edu [dot] my

Boon Heng Teh is a Senior Lecturer at the Faculty of Management, Multimedia University, Malaysia.

Hong Yong Hoe is a Lecturer at the Faculty of Management, Multimedia University, Malaysia.
E–mail: yhhong [at] mmu [dot] edu [dot] my

Tze San Ong (Ph.D.) is an Assistant Professor at the Faculty of Economics and Management Universities Putra Malaysia.

John P. Charlton (Ph.D.) is a Reader in Psychology with research interests in computer–related behavior and attitudes at the University of Bolton, United Kingdom.



R.A. Abdulla, 2003. “The uses and gratifications of the Internet among Arab students in Egypt,” Ph.D. dissertation, University of Miami (Fla.), at http://scholarlyrepository.miami.edu/dissertations/1955/, accessed 26 August 2013.

American Psychological Association, 1992. “Ethical principles of psychologists and code of conduct,” at http://www.apa.org/ethics/code/index.aspx, accessed 26 August 2013.

R.H. Anderson, C. Kedzie, T.K. Bikson, B.R. Keltner, S.A. Law, C. Panis, B.M. Mitchell, J. Pliskin, and P. Srinagesh, 1995. “Universal access of e–mail: Feasibility and societal implications,” Santa Monica, Calif.: Rand Corp., at http://www.rand.org/pubs/monograph_reports/MR650.html, accessed 26 August 2013.

ASEAN Connect, 2005. “ASEAN digital divide database,” at http://www.aseanconnect.gov.my/index.php?option=com_wrapper&Itemid=48, accessed 12 September 2006.

B. Bimber, 2000. “Measuring the gender gap on the Internet,” Social Science Quarterly, volume 81, number 3, pp. 868–876.

J.G. Blumler, 1979. “The role of theory in uses and gratification studies,” Communication Research, volume 6, number 1, pp. 9–36.
http://dx.doi.org/10.1177/009365027900600102, accessed 26 August 2013.

Central Intelligence Agency. 2004. “The world factbook,” at https://www.cia.gov/library/publications/the-world-factbook/, accessed 23 March 2009.

T.R. Charney, 1996. “Uses and gratifications of the Internet,” Master’s thesis, Michigan State University.

J.P. Charlton and I.D.W. Danforth, 2007. “Distinguishing addiction and high engagement in the context of online game playing,” Computers in Human Behavior, volume 23, number 3, pp. 1,531–1,548.
http://dx.doi.org/10.1016/j.chb.2005.07.002, accessed 26 August 2013.

J.P. Charlton, P. C–H Soh, P.H. Ang, and K.–W. Chew, 2012. “Religiosity, adolsescent Internet usage motives and addiction: An exploratory study,” Information, Communication & Society.
http://dx.doi.org/10.1080/1369118X.2012.735251, accessed 26 August 2013.

J. Choi, J. Watt, A. Dekkers, and S.–H. Park, 2004. “Motives of Internet uses: “Cross–cultural perspective — the US, the Netherlands, and S. Korea,” paper presented at the annual meeting of the International Communication Association (New Orleans, La.).

Y.J. Choi, 2001. “Investigating Koreans’ Internet use patterns and motivations, and exploring vulnerability of internet dependency,” Ph.D. dissertation, University of Southern Mississippi, at http://aquila.usm.edu/theses_dissertations/1881/, accessed 26 August 2013.

A. Colley, 2003. “Gender differences in adolescents’ perceptions of the best and worst aspects of computing at school,” Computers in Human Behavior, volume 19, number 6, pp. 673–682.
http://dx.doi.org/10.1016/S0747-5632(03)00022-0, accessed 26 August 2013.

J.N. Cummings and R. Kraut, 2002. “Domesticating computers and the Internet,” Information Society, volume 18, number 3, pp. 221–231.
http://dx.doi.org/10.1080/01972240290074977, accessed 26 August 2013.

Y.X. Deng, M. Hu, G.Q. Hu, L.S. Wang, and Z.Q. Sun, 2007. “An investigation of the prevalence of Internet addiction disorder in middle school students of Hunan province” [in Chinese], Zhonghua Liu Xing Bing Xue Za Zhi, volume 28, number 5, pp. 445–448.

D. Fallows, 2005. “How women and men Use the Internet” (28 December), Washington, D.C.: Pew Internet & American Life Project, at http://www.pewinternet.org/Reports/2005/How-Women-and-Men-Use-the-Internet.aspx, accessed 26 August 2013.

B.L. Fortson, J.R. Scotti, Y.–C. Chen, J. Malone, and K.S. Del Ben, 2007. “Internet use, abuse and dependence among students in a southeastern regional university,” Journal of American College Health, volume 56, number 2, pp. 137–144.

O.H. Gandy, 1994. “The information superhighway as the yellow brick road,” National Forum, volume 74, number 2, pp. 24–27.

E.F. Gross, 2004. “Adolescent Internet use: What we expect, what teens report,” Journal of Applied Developmental Psychology, volume 25, number 6, pp. 633–649, and at http://www.editlib.org/p/98517, accessed 26 August 2013.

E.J. Helspar, 2010. “Gendered Internet use across generations and life stages,” Communication Research, volume 37, number 3, pp. 352–374.
http://dx.doi.org/10.1177/0093650209356439, accessed 25 August 2013.

S.M.Y. Ho and M.C. Lee, 2001. “Computer usage and its relationship with adolescent lifestyle in Hong Kong,” Journal of Adolescence Health, volume 29, number 4, pp. 258–266.
http://dx.doi.org/10.1016/S1054-139X(01)00261-0, accessed 25 August 2013.

Y. Hong, X. Li, R. Mao, and B. Stanton, 2007. “Internet use among Chinese college students: Implications for sex education and HIV prevention,” CyberPsychology & Behavior, volume 10, number 2, pp. 161–169.
http://dx.doi.org/10.1089/cpb.2006.9973, accessed 26 August 2013.

A.S.C. Huang, 2004. “The bright and dark side of cyberspace: The paradoxical media effects of Internet use on gratifications, addictions, social and psychological well-being among Taiwan’s net–generation,” Ph.D. dissertation, Southern Illinois University (Carbondale), at http://sunzi.lib.hku.hk/ER/detail/hkul/3020454, accessed 26 August 2013.

C.–L. Hung, 2003. “Income, education, location and the Internet — The digital divide in China,” paper presented at the annual meeting of the International Communication Association (San Diego).

Internet World Stats, 2012. “Asia Internet use, population data and Facebook statistics,” at http://www.internetworldstats.com/stats3.htm#asia, accessed 13 March 2013.

L.A. Jackson, K.S. Ervin, P.D. Gardner, and N. Schmitt, 2001. “Gender and the Internet: Women communication and men searching,” Sex Roles, volume 44, numbers 5–6, pp. 363–379.
http://dx.doi.org/10.1023/A:1010937901821, accessed 26 August 2013.

R. Joiner, J. Gavin, M. Brosnan, J. Cromby, H. Gregory, J. Guiller, P. Maras, and A. Moon, 2012. “Gender, Internet experience, Internet identification and Internet anxiety: A ten year follow-up,” Cyberpsychology, Behavior, and Social Networking, volume 15, number 7, pp. 370–372.
http://dx.doi.org/10.1089/cyber.2012.0033, accessed 26 August 2013.

R. Joiner, J. Gavin, J. Duffield, M. Brosnan, C. Crook, A. Durndell, P. Maras, J. Miller, A.J. Scott, and P. Lovatt, 2005. “Gender, Internet identification, and Internet anxiety: Correlates of Internet use,” CyberPsychology & Behavior, volume 8, number 4, pp. 371–378.

S. Jones, C. Johnson-Yale, S. Millermaier, and F.S. Pérez, 2009. “U.S. college students’ Internet use: Race, gender and digital divides,” Journal of Computer–Mediated Communication, volume 14, number 2, pp. 244–264.
http://dx.doi.org/10.1111/j.1083-6101.2009.01439.x, accessed 26 August 2013.

E. Katz, J.G. Blumler, and M. Gurevitch, 1974. “Utilization of mass communication by the individual,” In: J.G. Blumler and E. Katz (editors). The uses of mass communications: Current perspectives on gratifications research. Beverly Hills, Calif.: Sage, pp. 19–32.

R. Kraut, W. Scherlis, T. Muckhopadhyay, J. Manning, and S. Kiesler, 1996. “The HomeNet field trial of residential Internet services,” Communications of the ACM, volume 39, number 12, pp. 55–63.
http://dx.doi.org/10.1145/240483.240493, accessed 26 August 2013.

E.C.Y. Kuo, A. Choi, and W.P. Lee, 2002. Singapore Internet project: Key findings of student panel study. Nanyang Technological University, School of Communication and Information.

J.C. Kwon, 2003. “A proposed model for use of the Internet and World Wide Web,” Ph.D. dissertation, University of Alabama.

A. Lenhart, M. Madden, and P. Hitlin, 2005. “Teens and technology: Youth are leading the transition to a fully wired and mobile nation” (27 July), Washington, D.C.: Pew Internet & American Life Project, at http://www.pewinternet.org/~/media/Files/Reports/2005/PIP_Teens_Tech_July2005web.pdf.pdf, accessed 26 August 2013.

L. Leung, 2004. “Net–generation attributes and seductive properties of the Internet as predictors of online activities and Internet addiction,” CyberPsychology & Behavior, volume 7, number 3, pp. 333–348.
http://dx.doi.org/10.1089/1094931041291303, accessed 26 August 2013.

N. Li and G. Kirkup, 2007. “Gender and cultural differences in Internet use: A study of China and the UK,” Computers & Education, volume 48, number 2, pp. 301–307.
http://dx.doi.org/10.1016/j.compedu.2005.01.007, accessed 26 August 2013.

C.–H. Lin and S.–F. Yu, 2008. “Adolescent Internet usage in Taiwan: Exploring gender differences,” Adolescence, volume 43, number 170, pp. 317–331.

S. Livingstone and M. Bober, 2005. “UK children go online: Final report of key project findings,“ London School of Economics and Political Science, at http://eprints.lse.ac.uk/399/, accessed 26 August 2013.

V.–h. Lo and R. Wei, 2005. “Exposure to Internet pornography and Taiwanese adolescents’ sexual attitudes and behavior,” Journal of Broadcasting & Electronic Media, volume 49, number 2, pp. 221–237.
http://dx.doi.org/10.1207/s15506878jobem4902_5, accessed 26 August 2013.

D. Madell and S. Muncer, 2004. “Gender differences iin the use of the Internet by English secondary school children,” Social Psychology of Education, volume 7, number 2, pp. 229–251.
http://dx.doi.org/10.1023/B:SPOE.0000018552.85903.4d, accessed 26 August 2013.

Malaysian Communications and Multimedia Commission (Suruhanjaya Komunikasi dan Multimedia Malaysia), 2008. “Household use of the Internet Survey 2008,” at http://www.apira.org/data/upload/HUIS08_02_oXJL4a.pdf, accessed 26 August 2013.

Malaysian Communications and Multimedia Commission (Suruhanjaya Komunikasi dan Multimedia Malaysia), 2005. “Household use of the Internet survey 2005,” Cyberjaya: Malaysian Communications and Multimedia Commission.

G.–J. Meerkerk, R.J.J.M. Van Den Eijnden, and H.F.L. Garretsen, 2006. “Predicting compulsive Internet use: It’s all about sex!” CyberPsychology & Behavior, volume 9, number 1, pp. 95–103.
http://dx.doi.org/10.1089/cpb.2006.9.95, accessed 26 August 2013.

W.S. Mitchell, 1999. “Social and psychological factors associated with Internet use in the home: A uses and gratifications study,” Ph.D. dissertation, Bowling Green State University.

H. Ono and M. Zavodny, 2003. “Gender and the Internet,” Social Science Quarterly, volume 84, number 1, pp. 111–121.
http://dx.doi.org/10.1089/cpb.2006.9.95, accessed 26 August 2013.

O. Palesh, K. Saltzman, and C. Koopman, 2004. “Internet use and attitudes towards illicit Internet use behavior in a sample of Russian college students,” CyberPsychology & Behavior, volume 7, number 5, pp. 553–558.

Z. Papacharissi and A. Rubin, 2000. “Predictors of Internet use,” Journal of Broadcasting & Electronic Media, volume 44, number 2, pp. 175–196.
http://dx.doi.org/10.1207/s15506878jobem4402_2, accessed 26 August 2013.

I. Park, 2004. “Internet usage of Korean and American students: A uses and gratifications approach,” Ph.D. dissertation, University of Southern Mississippi, at http://aquila.usm.edu/theses_dissertations/2378/, accessed 26 August 2013.

J.V. Pavlik, 1998. New media technology: Cultural and commercial perspectives. Second revised edition. Boston: Allyn and Bacon.

M. Schafgans, 2000. “Gender wage differences in Malaysia: Parametric and semiparametric estimation,” Journal of Development Economics, volume 63, number 2, pp. 351–378.
http://dx.doi.org/10.1016/S0304-3878(00)00114-0, accessed 26 August 2013.

P. Schumacher and J. Morahan–Martin, 2001. “Gender, Internet and computer attitudes and experiences,” Computers in Human Behavior, volume 17, number 1, pp. 95–110.
http://dx.doi.org/10.1016/S0747-5632(00)00032-7, accessed 26 August 2013.

L. Shashanni, 1997. “Gender differences in computer attitudes and use among college students,” Journal of Educational Computing Research, volume 16, number 1, pp. 37–51.

P. C–H Soh, Y.L. Yan, T.S. Ong, and B.H. Teh, 2012. “Digital divide amongst urban youths — Myth or reality?” Asian Social Science, volume 8, number 15, pp. 75–85; also at http://www.ccsenet.org/journal/index.php/ass/article/view/22648, accessed 26 August 2013.
http://dx.doi.org/10.5539/ass.v8n15p75, accessed 26 August 2013.

P. C–H Soh, R. Murali, P.M. Shingi, and K.W. Chew, 2007. “Understanding Internet uses and dependencies of youths — A holistic approach,” Cyberscape Journal, volume 5, number 2.

I. Song, D.R. LaRose, M.S. Eastin, and C.A. Lin, 2004. “Internet gratification and internet addiction: On the uses and abuses of the new media,” CyberPsychology & Behavior, volume 7, number 4, pp. 385–395.
http://dx.doi.org/10.1089/cpb.2004.7.384, accessed 26 August 2013.

S. Sun, 2004. “Internet use, involvement, and dependency,” Ph.D. dissertation, Kent State University.

T.S.H. Teo and V.K.G. Lim, 2000. “Gender differences in internet usage and task preferences,” Behaviour & Information Technology, volume 19, number 4, pp. 283–295.
http://dx.doi.org/10.1080/01449290050086390, accessed 26 August 2013.

A Tsitsika, E. Critselis, G. Kormas, A. Filippopoulou, D. Tounissidou, A. Freskou, T. Spiliopoulou, A. Louizou, E. Konstantoulaki, and D. Kafetzis, 2008. “Internet use and misuse: A multivariate regression analysis of the predictive factors of Internet use among Greek adolescents,” European Journal of Pediatrics, volume 168, number 6, pp. 655–665.
http://dx.doi.org/10.1007/s00431-008-0811-1, accessed 26 August 2013.

University of Southern California’s Annenberg School Center for the Digital Future, 2008. “The 2008 digital future report — Surveying the digital future: Year seven,” at http://www.digitalcenter.org/wp-content/uploads/2013/02/2008_digital_future_report-year7.pdf, accessed 26 August 2013.

University of Southern California’s Annenberg School Center for the Digital Future, 2005. “The digital future report 2005 — Surveying the digital future: Year five,” at http://www.digitalcenter.org/wp-content/uploads/2013/02/2005_digital_future_report-year5.pdf, accessed 26 August 2013.

Y. Wang, 2006. “Internet use among Chinese students and its implications for cross–cultural adaptation,” Ph.D. dissertation, Kent State University, at http://rave.ohiolink.edu/etdc/view?acc_num=kent1164921279, accessed 26 August 2013.

I.M. Wasserman and M. Richmond–Abbott, 2005. “Gender and the Internet: Causes of variation in access, level, and scope of use,” Social Science Quarterly, volume 86, number 1, pp. 252–270.
http://dx.doi.org/10.1111/j.0038-4941.2005.00301.x, accessed 26 August 2013.

E.B. Weiser, 2000. “The functions of Internet use and their social, psychological, and interpersonal consequences,” Ph.D. dissertation, Texas Technical University.

U. Wolfradt and J. Doll, 2001. “Motives of adolescents to use the Internet as a function of personality traits, personal and social factors,” Journal of Educational Computing Research, volume 24, number 1, pp. 13–27.
http://dx.doi.org/10.2190/ANPM-LN97-AUT2-D2EJ, accessed 26 August 2013.

M.L. Ybarra and K.J. Mitchell, 2005. “Exposure to Internet pornography among children and adolescents: A national project,” CyberPsychology & Behavior, volume 8, number 5, pp. 473–486.


Editorial history

Received 10 January 2013; revised 10 April 2013; accepted 20 August 2013.

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“Exploring gender differences in Malaysian urban adolescent Internet usage” by Patrick C–H Soh, Boon Heng Teh, Yong Hoe Hong, Tze San Ong, and John P. Charlton is licensed under a Creative Commons Attribution–NonCommercial 3.0 Unported License.

Exploring gender differences in Malaysian urban adolescent Internet usage
by Patrick C–H Soh, Boon Heng Teh, Yong Hoe Hong, Tze San Ong, and John P. Charlton.
First Monday, Volume 18, Number 9 - 2 September 2013

A Great Cities Initiative of the University of Illinois at Chicago University Library.

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